Photo Credit: Renqin Cai (UVA)

Welcome to Ruocheng Guo's homepage. Check out his blog here.

Ruocheng is a Ph.D. student @ Arizona State University, now he is affiliated with Data Mining and Machine Learning Lab, under supervision of Prof. Huan Liu.

Research Interests: Learning Causality with Data, Machine Learning and Social Media Mining.

Before joining ASU, Ruocheng received M.Sc degree in Electronic Engineering from the most beautiful Hong Kong University of Science and Technology in Hong Kong, China and B.Eng degree in Electrical Engineering from Huazhong University of Science and Technology in Wuhan, China.

Ruocheng Guo

Contact me through:
rguo12 at asu dot edu

Data Mining and Machine Learning Lab
Arizona State University
699 Mill Ave BYENG
Tempe, AZ 85281
USA

News

[June 2019] The first paper utilizing network information for deconfounding in observation data is out on arxiv! Please check out Ruocheng's work Learning Individual Treatment Effects from Networked Observational Data with Jundong Li and Dr. Huan Liu!
[April 2019] The coauthored paper Adaptive Unsupervised Feature Selection on Attributed Networks with Jundong Li, Chenghao Liu and Dr. Huan Liu got accepted in KDD 2019 as an oral paper!
[April 2019] A significantly revised version of A Survey of Learning Causality with Data: Problems and Methods is available!
[April 2019] I will talk about Learning Causality with Non-i.i.d. data in the ASU event, CASCADE Workshop/Retreat on Big Data Challenges, Techniques, and Applications.
[March 2019] The awesome-causality-index is mentioned by the Chinese social media publisher ZhuanZhi, check it out here if you can read Chinese.
[Jan 2019] I am going to join Etsy as a Ph.D. Data Science Intern in Summer 2019 mentored by Dr. Liangjie Hong, looking forward to meeting you in NYC.
[Dec 2018] The coauthored paper Hierarchical Attention Networks for Cyberbullying Detection on the Instagram Social Network with Lu Cheng and Dr. Liu got accepted in SDM 2019 as a full research paper!
[Oct 2018] The coauthored paper Protecting User Privacy: An Approach for Untraceable Web Browsing History and Unambiguous User Profiles with Ghazaleh Beigi, Alex Nou, Yanchao Zhang and Dr. Liu got accepted in WSDM 2019 as a full research paper!
[Sep 2018] A Survey of Learning Causality with Data: Problems and Methods is available on [arxiv]!
[Aug 2018] Ruocheng received the SIGIR travel grant for CIKM 2018!
[July 2018] The paper Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects got accepted in CIKM 2018 as a short paper! Looking forward to meeting you in Turin!
[June 2018] Ruocheng received the Engineering Graduate Fellowship from CIDSE, ASU!
[Apr 2018] The paper INITIATOR: Noise-contrastive Estimation for Marked Temporal Point Process got accepted in IJCAI-ECAI 2018!

Publications

Preprint

  • Learning Individual Treatment Effects from Networked Observational Data
    Ruocheng Guo, Jundong Li and Huan Liu
    Under Review
    [arxiv] [code]

Conference Papers

  • Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects
    Ruocheng Guo*, Vineeth Rakesh*, Raha Moraffah, Nitin Agarwal and Huan Liu (* Equal Contribution)
    CIKM 2018 (short paper, acceptance rate 23.4%)
    [arxiv] [pdf] [poster] [code]

  • INITIATOR: Noise-contrastive Estimation for Marked Temporal Point Process
    Ruocheng Guo, Jundong Li and Huan Liu
    IJCAI-ECAI 2018 (acceptance rate 20.5%)
    [pdf]

  • Strongly Hierarchical Factorization Machines and ANOVA Kernel Regression
    Ruocheng Guo, Hamidreza Alvari and Paulo Shakarian
    SDM 2018 (acceptance rate 23.2%)
    [arxiv] [appendix]
    A 20k sample from When Do You Retweet dataset [Download]

  • A Comparison of Methods for Cascade Prediction
    Ruocheng Guo and Paulo Shakarian
    ASONAM 2016
    [arxiv]

  • Towards Order-of-magnitude Cascade Prediction
    Ruocheng Guo, Elham Shaabani, Abhinav Bhatnagar and Paulo Shakarian
    ASONAM 2015
    [arxiv]

  • Adaptive Unsupervised Feature Selection on Attributed Networks
    Jundong Li, Ruocheng Guo, Chenghao Liu and Huan Liu
    KDD 2019
    [To appear]

  • Hierarchical Attention Networks for Cyberbullying Detection on the Instagram Social Network
    Lu Cheng, Ruocheng Guo, Yasin Silva, Deborah Hall and Huan Liu
    SDM 2019
    [pdf]

  • Protecting User Privacy: An Approach for Untraceable Web Browsing History and Unambiguous User Profiles
    Ghazaleh Beigi, Ruocheng Guo, Alex Nou, Yanchao Zhang and Huan Liu
    WSDM 2019
    [pdf][KDNuggets]

  • Detecting Pathogenic Social Media Accounts without Content or Network Structure
    Elham Shaabani, Ruocheng Guo and Paulo Shakarian
    ICDIS 2018 (Best Poster)
    [pdf]

  • Temporal Analysis of Influence to Predict Users’ Adoption in Online Social Networks
    Ericsson Marin, Ruocheng Guo and Paulo Shakarian
    SBP 2017
    [arxiv]

Journal Papers

  • Toward Early and Order-of-magnitude Cascade Prediction in Social Networks
    Ruocheng Guo, Elham Shaabani, Abhinav Bhatnagar and Paulo Shakarian
    SNAM 2016
    [arxiv]

  • Using Network Motifs to Characterize Temporal Network Evolution Leading to Diffusion Inhibition
    Soumajyoti Sarkar, Ruocheng Guo and Paulo Shakarian
    SNAM 2019
    [arxiv]

  • Understanding and Forecasting Lifecycle Events in Information Cascades
    Soumajyoti Sarkar, Ruocheng Guo and Paulo Shakarian
    SNAM 2017
    [arxiv]

Book

Workshop Papers

Website based on Plain Academic